Autonomous vehicles, such as vehicles which do not require a human driver, can be used to aid in the transport of passengers or items from one location to another. An important component of an autonomous vehicle system is the perception system, which allows the vehicle to perceive and interpret its surroundings using cameras, radar, sensors, and other similar devices. The perception system executes numerous decisions while the autonomous vehicle is in motion, such as speeding up, slowing down, stopping, turning, etc. Autonomous vehicles can also use the cameras, sensors, and global positioning devices to gather and interpret images and sensor data about its surrounding environment, e.g., pedestrians, bicyclists, other vehicles, parked cars, trees, buildings, etc. These systems generally use object recognition to make the above determinations and recognitions.
Object recognition is used to determine which, if any, of a set of known objects is present in an image of an observed scene. The object recognition system builds a database of known objects. Information used to build the database may come from controlled observation of known objects, or it may come from an aggregation of objects observed in scenes without formal supervision. Then, a new observation of a previously viewed object is matched with its representation in the database.